Generative AI Engineering Bootcamp
Build production-grade GenAI systems — RAG pipelines, agents, fine-tuning, and evals — alongside engineers from top AI companies.
Next cohort begins in
What you’ll learn
Outcomes, not just content
- ✓Design and deploy RAG systems over enterprise data
- ✓Fine-tune open-source LLMs with LoRA and QLoRA
- ✓Build multi-agent systems with tool use and memory
- ✓Implement evals, guardrails, and observability
- ✓Ship a capstone GenAI product reviewed by senior engineers
Curriculum
6 modules · built for depth
01Foundations of Modern LLMs
3 topics- Transformer internals
- Tokenization & embeddings
- Prompt engineering at scale
02Retrieval-Augmented Generation
3 topics- Vector databases
- Chunking strategies
- Hybrid search & re-ranking
03Agents & Tool Use
3 topics- ReAct & Plan-Execute
- Function calling
- Multi-agent orchestration
04Fine-Tuning & Alignment
3 topics- Instruction tuning
- LoRA / QLoRA
- RLHF & DPO
05Evals & Production
3 topics- LLM-as-judge
- Guardrails
- Cost & latency optimization
06Capstone Project
3 topics- Scoped product build
- Code review with mentors
- Demo day
Prerequisites
- ›Working Python knowledge
- ›Familiarity with APIs and basic ML concepts
FAQ
Generative AI Engineering Bootcamp — FAQ
Do I need prior ML experience?
No — you need working Python and comfort with APIs. We bring you up to speed on the ML fundamentals needed to work with LLMs in the first week.
Will I use real APIs or just open models?
Both. We build with OpenAI/Anthropic APIs, open models via Ollama and HuggingFace, and cover when to choose each in production.
What kind of capstone will I ship?
A scoped GenAI product of your choice — past cohorts have shipped legal RAG tools, AI sales agents, and internal dev copilots. Reviewed 1:1 with a senior engineer.
Are cohort sizes small?
Yes — hard cap of 30 learners per cohort. You get direct mentor time, not a broadcast.
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